Impact of multiple sound types on environmental sound classification

A wireless sensor network equipped with microphones can be used for context awareness by classifying sound events in the target environment. This classification will become less accurate when more than one sound can be heard at the same time. We conduct a series of experiments in which we mix different sound types in order to see how high this influence is. We conclude, that in most cases, the classifier will become unreliable if other sounds with the same loudness are audible within a range of less than five times the distance of the main sound from the microphone.